85、Hierarchical Clustering: An In - Depth Exploration

Hierarchical Clustering: An In - Depth Exploration

1. Introduction to Hierarchical Clustering

Hierarchical clustering is a powerful technique in data analysis. It is designed in an iterative and distributed way, with two main approaches: top - down and bottom - up. One of its significant advantages is that it doesn’t require prior knowledge about the number of clusters. This characteristic allows for faster clustering computations compared to some other methods.

Hierarchical clustering creates cluster structures in the form of a dendrogram. In this structure, the leaves are considered as samples, and the root of the structure represents a cluster that contains all the samples.

2. Hierarchical Clustering Schemes

2.1 Agglomerative